Finite Element Modeling of Thermal Insulation Effects in a Borehole Thermal Energy Storage
Bibliographic record
Abstract
A recent application of borehole thermal energy storage (BTES) technology to residential properties in Canada shows a significant reduction in the use of natural gas thereby saving energy consumption and reducing the generation of greenhouse gases. However, due to the construction principles of the BTES, the systems are not thermally insulated on the sides and the bottom. Hence, almost all injected heat into a single borehole dissipates into surrounding ground over the night when heat injection stops. In order to minimize thermal energy dissipation, construction of thermal insulation barrier using expanded perlite aggregate (EPA) was proposed to reduce the heat flow and increase the efficiency by providing a soilcrete thermal insulation layer around the BTES system. The initial research proposed to utilize jet grouting technology for construction of the EPA mixed soilcrete thermal insulation layer. However, due to the nature of the jet grouting technology, the construction process of jet grouting is lengthy and therefore expensive for this application. Besides, the high buoyancy forces exerted created potential risks of aggregate segregation. To improve constructability and to mitigate the risks of aggregate segregation, this research proposes to employ one pass deep trenching method construction of the soilcrete thermal insulation layer.the risks of aggregate segregation, this research proposes to employ one pass deep trenching method construction of the soilcrete thermal insulation layer. Full-scale numerical models using two finite element analysis (FEA) software: Abaqus and Temp/W were developed to investigate the effectiveness of the soilcrete insulation layer constructed with one pass deep trenching method. The numerical model provides theoretical evidence for the application of soilcrete thermal insulation layer in reducing the thermal energy loss and thereby improving the efficiency of the system. The FEA modeling results showed that the thermal insulating soilcrete successfully entrapped more thermal energy within the system compared to the system without thermal insulation and reduced the annual average heat flux up to 46 % with three-meter thickness insulation barrier.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".